code: def test_target_mean_std(
      self, args, data, normalized_data, normalized_target, mean, std
  ):
      dtype = data[args["keys"][0]].dtype
      normalizer = ReferenceBasedNormalizeIntensityd(
          keys=args["keys"],
          ref_key=args["ref_key"],
          channel_wise=args["channel_wise"],
          dtype=dtype,
      )
      res_data = normalizer(data)
  
      img = np.round(convert_to_numpy(res_data[args["keys"][0]]), 3)
      normalized_data = np.round(convert_to_numpy(normalized_data), 3)
  
      target = np.round(convert_to_numpy(res_data[args["keys"][1]]), 3)
      normalized_target = np.round(
          convert_to_numpy(normalized_target), 3
      )
  
      assert_allclose(img, normalized_data)
      assert_allclose(target, normalized_target)
  
      assert_allclose(np.round(res_data["mean"], 3), mean)
      assert_allclose(np.round(res_data["std"], 3), std)
  
file_path: MONAI/tests/test_reference_based_normalize_intensity.py
imports: from __future__ import annotations
  import unittest
  import numpy
  from parameterized import parameterized
  from monai.apps.reconstruction.transforms.dictionary import ReferenceBasedNormalizeIntensityd
  from monai.utils.type_conversion import convert_to_numpy
  from tests.utils import TEST_NDARRAYS_NO_META_TENSOR, assert_allclose
label_desc: Use image node_id 1 for calling the TestDetailedNormalizeIntensityd obj's underlying member method code with example usage: obj.test_target_mean_std(args, data, normalized_data, normalized_target, mean, std) without return types